matplotlib.axis.XAxis.get_offset_text() Function
The XAxis.get_offset_text() function in axis module of matplotlib library is used to get the axis offsetText as a Text instance.
Syntax: XAxis.get_offset_text(self)
Parameters: This method does not accepts any parameter.
Return value: This method returns the axis offsetText as a Text instance.
Below examples illustrate the matplotlib.axis.Axis.get_offset_text() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import matplotlib.text fig, ax = plt.subplots() ax.plot([5,1], label="Label 1") ax.plot([3,0], label="Label 2") legend = ax.legend(loc="upper right") offset = matplotlib.text.OffsetFrom(legend, (1.0, 0.0)) ax.annotate("String - Info", xy = (0,0), size = 14, xycoords = 'figure fraction', xytext = (0,-20), textcoords = offset, horizontalalignment = 'right', verticalalignment = 'top') fig.canvas.draw() fig.suptitle('Matplotlib.axis.Axis.get_offset_text()\n\ Function Example') ax.grid() print("Value of get_offset_text() :",ax.xaxis.get_offset_text()) plt.show() |
Output:
Value of get_offset_text() : Text(1, 24.911111111111108, '')
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np fig, geeeks = plt.subplots() t = np.arange(0.0, 5.0, 0.001) s = np.cos(3 * np.pi * t) line = geeeks.plot(t, s, lw = 2) # Annotation geeeks.annotate('Local Max', xy =(3.3, 1), xytext =(3, 1.8), arrowprops = dict(facecolor ='green', shrink = 0.05),) geeeks.set_ylim(-2, 2) fig.suptitle('Matplotlib.axis.Axis.get_offset_text()\n\ Function Example') geeeks.grid() print("Value of get_offset_text() :",geeeks.xaxis.get_offset_text()) plt.show() |
Output:
Value of get_offset_text() : Text(1, 0, '')
Matplotlib.axis.XAxis.get_offset_text() function in Python
Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and is used for working with the broader SciPy stack.